4 présentations

• 
  10h30 - 10h55

  Convex Optimization for Interference Management in Integrated HAPS-Terrestrial 6G Networks

  • Afsoon Alidadi Shamsabadi, prés.,

  The rapid increase in mobile traffic and the emergence of novel use cases have led to a pressing need for network architectures that can cope with the forthcoming network trend in sixth-generation (6G) and beyond wireless networks. In this context, non-terrestrial networks (NTNs), in particular, high altitude platform stations (HAPS), have emerged as a promising architecture to be integrated with existing terrestrial wireless networks, incorporating powerful technologies into communication systems. However, harmonized spectrum integrated networks, where different tiers share the same frequency band, are prone to performance degradation due to inter-tier interference propagation. To address this issue, efficient interference management techniques must be implemented. The interference management algorithms must ensure enhancing the network's overall performance by optimizing key network parameters such as radio resources, antenna array geometry, etc. Diverse optimization problems can be formulated in this context, each with a distinct objective and impact on network performance. However, in most scenarios, the formulated problems are strictly non-convex and NP-hard to be solved for the optimal solution. Hence, various reformulation linearization techniques are required to transform the original problems to equivalent approximated convex forms which can be solved for optimal solution, which is the suboptimal solution of the original problem.

• 
  10h55 - 11h20

  Integrated Computation Offloading, UAV Trajectory Control, and Resource Allocation against Jamming in SAGIN

  • Minh Dat Nguyen, prés., UQAM
  • Wessam Ajib, University of Quebec at Montreal (UQAM)
  • Wei-Ping Zhu, Concordia University
  • Gunes Karabulut Kurt, Polytechnique Montreal

  In this work, we study the computation offloading problem against an active attacker in space-air-ground integrated networks (SAGIN), where joint optimization of partial computation offloading, unmanned aerial vehicle (UAV) trajectory control, computation and resource allocation is performed. Our design aims to minimize the maximum computation time of individual tasks among ground users while satisfying energy consumption constraints. To tackle the underlying non-convex optimization problem, we use the alternating optimization approach to iteratively solve three sub-problems, namely, partial offloading control and bit allocation over time slots, computation resource and bandwidth allocation, and UAV trajectory control, until convergence. Furthermore, the successive convex approximation method is employed to solve the non-convex sub-problems and improve the resilience of the SAGIN against active attacks. Via extensive numerical studies, we illustrate the effectiveness of our proposed design compared to baselines under the effect of an active attacker.

• 
  11h20 - 11h45

  Model Predictive Control-Based Routing in High-Throughput Satellites

  • Olivier Bélanger, prés., Polytechnique Montréal
  • Olfa Ben Yahia, Polytechnique Montréal
  • Stéphane Martel, MDA
  • Antoine Lesage-Landry, Polytechnique Montréal
  • Gunes Karabulut Kurt, Polytechnique Montréal

  The recent deployment of low Earth orbit mega-constellations has yielded an increase in the data rate demanded of each satellite, furthering the use of High Throughput Satellites (HTS). Current state-of-the-art satellites have limited data rates, which pose a challenge as the number of users is increasing. To meet the demand for increased data rates, advanced routing techniques have been developed for the next generation of satellites. There is a gap in the literature on the internal routing scheme of a single multi-processing unit-based HTS to reach Terabit/second transmission rates. To address it, we design an optimal flow allocation and priority queue scheduling method under a model predictive control framework. We formulate the problem as a multi-commodity flow instance in which the commodities are incoming data streams with different priorities, the source is the uplink beam, and the sinks include both the downlink beam and the discarded packets. Our approach minimizes packet loss and allows for real-time routing adaptation in response to incoming information and exogenous uncertainty. Each stage of this model is meticulously assessed for both routing and computational performance, with the results compared to a reference model and traditional methods in numerical simulation.

• 
  11h45 - 12h10

  Radio Resources Management for NB-IoT-Enabled Multi-Microgrid Systems

  • Abdullah Othman, prés., ÉTS Montréal
  • Victor Evangelista, Ericsson
  • Georges Kaddoum, ÉTS Montréal
  • Au Minh, IREQ
  • Basile Agba, IREQ

  Efficient integration of renewable resources is vital for the smart grid's transition from fossil fuels. Multi-Microgrid Systems (MMSs), powered by distributed energy resources (DERs), offer a promising path. Robust radio resource management in MMS communications is crucial. This study showcases narrow-band IoT's coverage enhancement for MMS networks, formulating a problem to maximize DERs' weighted sum-rate with varied quality of service classes. We use tools from stochastic geometry to model the MMS networks. Next, difference-of-convex tools for power control and a distributed heuristic for sub-carrier scheduling are employed, combining data-driven methods and mixed-integer nonlinear programming for network size compression and coordination.